Command line Training Set First Motif Summary of Motifs Termination Explanation


MEME - Motif discovery tool

MEME version 3.0 (Release date: 2002/04/02 00:11:59)

For further information on how to interpret these results or to get a copy of the MEME software please access http://meme.sdsc.edu.

This file may be used as input to the MAST algorithm for searching sequence databases for matches to groups of motifs. MAST is available for interactive use and downloading at http://meme.sdsc.edu.


REFERENCE

If you use this program in your research, please cite:

Timothy L. Bailey and Charles Elkan, "Fitting a mixture model by expectation maximization to discover motifs in biopolymers", Proceedings of the Second International Conference on Intelligent Systems for Molecular Biology, pp. 28-36, AAAI Press, Menlo Park, California, 1994.


TRAINING SET

DATAFILE= /home/max/var/seq/5noambigous.fa
ALPHABET= ACGT
Sequence name            Weight Length  Sequence name            Weight Length  
-------------            ------ ------  -------------            ------ ------  
1                       1.0000   2000  2                       1.0000   1962  
3                       1.0000   2000  4                       1.0000   2000  
5                       1.0000   2000  6                       1.0000   1908  


COMMAND LINE SUMMARY

This information can also be useful in the event you wish to report a
problem with the MEME software.

command: meme /home/max/var/seq/5noambigous.fa -dna 

model:  mod=         zoops    nmotifs=         1    evt=           inf
object function=  E-value of product of p-values
width:  minw=            8    maxw=           50    minic=        0.00
width:  wg=             11    ws=              1    endgaps=       yes
nsites: minsites=        2    maxsites=        6    wnsites=       0.8
theta:  prob=            1    spmap=         uni    spfuzz=        0.5
em:     prior=   dirichlet    b=            0.01    maxiter=        50
        distance=    1e-05
data:   n=           11870    N=               6
strands: +
sample: seed=            0    seqfrac=         1
Letter frequencies in dataset:
A 0.305 C 0.184 G 0.196 T 0.316 
Background letter frequencies (from dataset with add-one prior applied):
A 0.305 C 0.184 G 0.196 T 0.316 


P N
MOTIF 1
    width = 15     sites = 4     llr = 69     E-value = 1.2e+002

SimplifiedA:::8a:::3::a3::
pos.-specificC8:53:aa3:aa:3:a
probabilityG::5::::5:::::::
matrixT3a:::::38:::5a:
.
bits 2.4     
2.2     
2.0     
1.7         
Information 1.5           
content 1.2           
(24.8 bits)1.0             
0.7              
0.5               
0.2               
0.0
.
Multilevel CTCAACCGTCCATTC
consensus TGCCAA
sequence TC
.
NAME   START P-VALUE    SITES
 
518693.91e-10 CTAAATGAATCTCAACCGTCCATTCATTAGAGAAG
418228.07e-10 GAGATTGAATCTGAACCGTCCATTCTGGGAAGGGC
3313.75e-08 GAAGGAAACTTTGAACCTTCCACTCTTCGGGTCTC
113733.75e-08 CCCTAATGGGCTCCACCCACCAATCCCGCTACCTC


Motif 1 block diagrams

NameLowest
p-value
   Motifs
5 3.9e-10

1
4 8.1e-10

1
3 3.7e-08

1
1 3.7e-08

1
SCALE
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
1 25 50 75 100 125 150 175 200 225 250 275 300 325 350 375 400 425 450 475 500 525 550 575 600 625 650 675 700 725 750 775 800 825 850 875 900 925 950 975


Motif 1 in BLOCKS format

BL   MOTIF 1 width=15 seqs=4
5                       ( 1869) CTCAACCGTCCATTC  1 
4                       ( 1822) CTGAACCGTCCATTC  1 
3                       (   31) TTGAACCTTCCACTC  1 
1                       ( 1373) CTCCACCCACCAATC  1 
//


Motif 1 position-specific scoring matrix

log-odds matrix: alength= 4 w= 15 n= 11786 bayes= 11.5243 E= 1.2e+002 
  -865    203   -865    -34 
  -865   -865   -865    166 
  -865    144    135   -865 
   130     44   -865   -865 
   171   -865   -865   -865 
  -865    244   -865   -865 
  -865    244   -865   -865 
  -865     44    135    -34 
   -28   -865   -865    125 
  -865    244   -865   -865 
  -865    244   -865   -865 
   171   -865   -865   -865 
   -28     44   -865     66 
  -865   -865   -865    166 
  -865    244   -865   -865 


Motif 1 position-specific probability matrix

letter-probability matrix: alength= 4 w= 15 n= 11786 E= 1.2e+002 
 0.000760  0.748588  0.000488  0.250164 
 0.000760  0.000458  0.000488  0.998294 
 0.000760  0.499212  0.499241  0.000788 
 0.748889  0.249835  0.000488  0.000788 
 0.998266  0.000458  0.000488  0.000788 
 0.000760  0.997965  0.000488  0.000788 
 0.000760  0.997965  0.000488  0.000788 
 0.000760  0.249835  0.499241  0.250164 
 0.250136  0.000458  0.000488  0.748917 
 0.000760  0.997965  0.000488  0.000788 
 0.000760  0.997965  0.000488  0.000788 
 0.998266  0.000458  0.000488  0.000788 
 0.250136  0.249835  0.000488  0.499541 
 0.000760  0.000458  0.000488  0.998294 
 0.000760  0.997965  0.000488  0.000788 





Time 24.43 secs.


P N
SUMMARY OF MOTIFS



Combined block diagrams: non-overlapping sites with p-value < 0.0001

NameCombined
p-value
   Motifs
1 7.44e-05

1
2 7.01e-01

3 7.44e-05

1
4 1.60e-06

1
5 7.76e-07

1
6 3.20e-01

SCALE
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
1 25 50 75 100 125 150 175 200 225 250 275 300 325 350 375 400 425 450 475 500 525 550 575 600 625 650 675 700 725 750 775 800 825 850 875 900 925 950 975


Stopped because nmotifs = 1 reached.


CPU: birnbaum


EXPLANATION OF MEME RESULTS

The MEME results consist of:

MOTIFS

For each motif that it discovers in the training set, MEME prints the following information:


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